Flexible fibers, such as biomass particles and glass fibers, are critical raw materials in the
energy and composites industries. Assemblies of the fibers show strong interlocking, non …

The disordered nature of granular materials poses great difficulty to the accurate
characterization of microscopic structures. Despite numerous handcrafted structural …

Data-driven surrogate modeling provides a new way to characterize and predict the
mechanical behavior of materials. However, pure data-driven models tend to suffer from …

In thermal analysis modeling, the finite element method (FEM) is commonly used; however,
it incurs high computational costs and complicates the global optimization of thermal …

Constitutive models are considered a key prerequisite to investigate the thermal deformation
behavior of materials. Accurate identification of their parameters is crucial for enhancing the …

Determining the parameters of constitutive models is typically a material-specific process
that requires recalibration when the material changes. This procedure becomes notably time …

This study presents a physics-informed neural network (PINN) that captures the elasto-
plastic behaviour of soils under complex strain and stress paths. The PINN uses the void …